code: def test_bayesopt_batch(parameters, results):
      gpyopt = GPyOpt(max_concurrent=10)
      gpyopt.domain = gpyopt._initialize_domain(parameters)
      gpyopt.lower_is_better = True
      X, y, y_var = GPyOpt._prepare_data_for_bayes_opt(
          parameters, results
      )
      domain = gpyopt._initialize_domain(parameters)
      batch = gpyopt._generate_bayesopt_batch(
          X, y, lower_is_better=True, domain=domain
      )
  
      assert batch.shape == (10, 4)
  
imports: import sherpa
  import pandas
  import pytest
  import numpy
  import collections
  import GPyOpt
  from sherpa.algorithms.bayesian_optimization import GPyOpt
  from sherpa.algorithms import Repeat
label_desc: Use image node_id 14 for calling a global function with example usage: test_bayesopt_batch(parameters, results) without return types